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Navigation in collection of Photos
Blekinge Institute of Technology, School of Engineering.
Blekinge Institute of Technology, School of Engineering.
2011 (English)Independent thesis Advanced level (degree of Master (Two Years))Student thesis
Abstract [en]

We present a methodology to navigate viewing of a city block or any realistic outdoor structure by collection of images. The methodology implement intuitive navigation commands like as left, right, forward or backward to change the viewing position. In the thesis we used a collection of images from Gräsvik campus of Blekinge Institute of Technology and two commands of left and right were evaluated. The method is based on finding the camera position of each image in the collection. These positions have a relative distance to each other as far as no other information such as calibration data is used. For left and right navigation, two similar images to the image of the view point are found by searching for the two most correlated ones among collection of all images. Some of correspondent points of the three images (the view point image and the two most correlated images in the collection) are found by scale invariant feature transform (SIFT) method. Using the correspondent points between each two image a fundamental matrix, rotation, translation and camera positions are calculated. We used random sample consensus (RANSAC) method in calculation of the fundamental matrix which excludes the outliers of correspondent point in favor of obtaining a more robust result. The proposed algorithm is tested on large variety of images which are taken from the BTH gräsvik campus theme where all these images are varying in similarity. The obtained results from a GUI window are displayed with brief explanation.

Place, publisher, year, edition, pages
2011. , 29 p.
Keyword [en]
SIFT, RANSAC, Fundamental Matrix, Navigation, Automatic Image Similarity Measure, 3D Controls
National Category
Signal Processing
URN: urn:nbn:se:bth-2449Local ID: diva2:829726
Available from: 2015-04-22 Created: 2011-04-12 Last updated: 2015-06-30Bibliographically approved

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